Data Functionalization for Gas Chromatography in Python

Autor/inn/en	Green, Michael; Chen, Xiaobo
Titel	Data Functionalization for Gas Chromatography in Python
Quelle	In: Journal of Chemical Education, 97 (2020) 4, S.1172-1175 (4 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Chen, Xiaobo)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0021-9584
DOI	10.1021/acs.jchemed.9b00818?ref=pdf
Schlagwörter	Undergraduate Students; Data; Chemistry; Programming Languages; Data Analysis; College Science; Science Instruction; Science Activities; Missouri (Kansas City) + Suchen Sie Ihr Suchwort? Daten; Chemie; Auswertung; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht
Abstract	For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop. Furthermore, students should be fluent in methodologies that can translate to domains beyond their undergraduate curriculum. In this technology report, we demonstrate data functionalization in the Python programming language via data derived from gas chromatography. The programming approach to data analysis is designed to be flexible in order to allow students to take the lessons learned herein and apply them to novel systems outside of the experiment and outside of the academy. (As Provided).
Anmerkungen	Division of Chemical Education, Inc. and ACS Publications Division of the American Chemical Society. 1155 Sixteenth Street NW, Washington, DC 20036. Tel: 800-227-5558; Tel: 202-872-4600; e-mail: eic@jce.acs.org; Web site: http://pubs.acs.org/jchemeduc
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01